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Design and Analysis of an MST-Based Topology
Control Algorithm
Ning Li and Jennifer HouNing Li and Jennifer HouDepartment of Computer ScienceDepartment of Computer Science
University of Illinois at Urbana-ChampaignUniversity of Illinois at [email protected]@cs.uiuc.edu, [email protected], [email protected]
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OutlineOutline• Motivation• Topology Control• LMST: Local Minimum Spanning Tree• Simulation Study• Future Work
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MotivationsMotivations
(1) No Topology Control (2) With Topology Control
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R&D Roadmap and OpportunitiesR&D Roadmap and Opportunities
Application Layer
Transport Layer
Network Layer
MACLayer
Physical Layer
PowerAdjustment
Channels Selection (frequency/code)
Directional Beam-Forming
GPSPositioning & Synchronizing
Scheduling Contention Resolution
Topology Control
Routing
QoS Mapping(e.g. bounded delay)
Maintain connectivity using the minimum transmission power.Maintain connectivity by moving some “router” nodes to fill in the“hole”.Enable nodes to self-organize themselves into clusters.Load balance with power consideration
Realize Service Differentiation Provide bounded transmission delay
ErrorControl
DataAggregation/Computation
AdmissionControl
Integrated real time scheduling
and power control
Maximize information throughput but not data throughput
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TopologyTopology ControlControl Observations
Almost all ad-hoc routing algorithms rely on the cache to inexplicitly build an underlying topology.
Many broadcast/multicast algorithms for ad-hoc wireless networks maintain some kind of underlying topology, upon which the multicast tree/mesh can be built.
Routing
MAC / Power-controlled MAC
TopologyControl
Topology control can achieve: Global connectivity Low energy consumption Low interference High throughput
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Design GuidelinesDesign Guidelines• Network connectivity should be
preserved.• Bi-directional links are preferred. • Algorithms should be distributed.• To be immune to the impact of
mobility, the algorithm should depend on local information.
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LMST:LMST:Local Minimum Spanning TreeLocal Minimum Spanning Tree• Static wireless multihop networks.• Transmission power can be adjusted.• Each node knows its own position. • Each node will build its own minimum
spanning tree in its neighborhood and only retain those one-hop neighbors on the tree as its neighbors in the final topology.
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LMSTLMST• Visible neighborhood: the set of nodes that node u can
reach by using the maximum transmission power.• Information collection: Each node broadcast periodically a
Hello message using its maximal transmission power.• Topology construction
– Each node applies Prim’s algorithm independently to obtain its local minimum spanning tree.
– Each node takes all the one-hop, on-tree nodes as its neighbors.
– The network topology under LMST is all the nodes in V and their individually perceived neighbor relations.
• Determination of transmission power: a node transmits using the power that can reach its farthest neighbor.
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LMST PropertiesLMST Properties• The resulting topology preserves the
connectivity.• After removal of asymmetric links, all
links are bi-directional and the connectivity is still preserved.
• The degree of any node is bounded by 6.
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LMST: ExampleLMST: Example
w5
w3
w1
w7
w6
u
w4
w2
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Uni-directional LinksUni-directional Links
u v
w4
d
dmax
w3
w2
w1
dmax
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ConnectivityConnectivity
• G0 is connected with some uni-directional links.
• We can either add extra links into G0 so that all uni-directional links become bi-directional or delete all uni-directional links in G0.
• Both approaches give us connected graph with bi-directional links.
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SimulationsSimulations
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Simulations (Cont.)Simulations (Cont.)
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Dealing with MobilityDealing with Mobility
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Future WorkFuture Work• Extend LMST to mobile networks.• Build the multicast/broadcast
protocol upon LMST.• Implement LMST on a Motes testbed
at UIUC.
